ArticlePLoS computational biology2012
Spike-timing dependence of structural plasticity explains cooperative synapse formation in the neocortex.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Two-factor synaptic plasticity enables memory consolidation during neuronal burst firing.PNAS nexus · 2026Article
- Time delays in computational models of neuronal and synaptic dynamics.Frontiers in computational neuroscience · 2025Article
- Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity.PLoS computational biology · 2024Article
- Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST.Frontiers in neuroinformatics · 2023Article
- Sequence learning, prediction, and replay in networks of spiking neurons.PLoS computational biology · 2022Article
- Spike-Timing-Dependent Plasticity Mediated by Dopamine and its Role in Parkinson's Disease Pathophysiology.Frontiers in network physiology · 2022Review
- Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions.PLoS computational biology · 2021Article
- Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring.Frontiers in computational neuroscience · 2020Article
- Self-organized reactivation maintains and reinforces memories despite synaptic turnover.eLife · 2019Article
- Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder.Frontiers in computational neuroscience · 2019Article
- A Soft-Pruning Method Applied During Training of Spiking Neural Networks for In-memory Computing Applications.Frontiers in neuroscience · 2019Article
- Concurrence of form and function in developing networks and its role in synaptic pruning.Nature communications · 2018Article
- Multicontact Co-operativity in Spike-Timing-Dependent Structural Plasticity Stabilizes Networks.Cerebral cortex (New York, N.Y. : 1991) · 2018Article
- Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of NeoHebbian Three-Factor Learning Rules.Frontiers in neural circuits · 2018Review
- Opposing Effects of Neuronal Activity on Structural Plasticity.Frontiers in neuroanatomy · 2016Review
- Structural Plasticity, Effectual Connectivity, and Memory in Cortex.Frontiers in neuroanatomy · 2016Article
- Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity.Frontiers in neural circuits · 2016Article
- Formation and Maintenance of Robust Long-Term Information Storage in the Presence of Synaptic Turnover.PLoS computational biology · 2015Article
- Network Plasticity as Bayesian Inference.PLoS computational biology · 2015Article
- Reconstruction of recurrent synaptic connectivity of thousands of neurons from simulated spiking activity.Journal of computational neuroscience · 2015Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Structural plasticity governs the long-term development of synaptic connections in the neocortex. While the underlying processes at the synapses are not fully understood, there is strong evidence that a process of random, independent formation and pruning of excitatory synapses can be ruled out. Instead, there must be some cooperation between the synaptic contacts connecting a single pre- and postsynaptic neuron pair. So far, the mechanism of cooperation is not known. Here we demonstrate that local correlation detection at the postsynaptic dendritic spine suffices to explain the synaptic cooperation effect, without assuming any hypothetical direct interaction pathway between the synaptic contacts. Candidate biomolecular mechanisms for dendritic correlation detection have been identified previously, as well as for structural plasticity based thereon. By analyzing and fitting of a simple model, we show that spike-timing correlation dependent structural plasticity, without additional mechanisms of cross-synapse interaction, can reproduce the experimentally observed distributions of numbers of synaptic contacts between pairs of neurons in the neocortex. Furthermore, the model yields a first explanation for the existence of both transient and persistent dendritic spines and allows to make predictions for future experiments.
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